{"id":52412,"date":"2026-07-17T12:16:00","date_gmt":"2026-07-17T10:16:00","guid":{"rendered":"https:\/\/www.gesi.de\/ai-and-digitalization-in-hazardous-materials-management-opportunities-limitations-and-a-look-ahead\/"},"modified":"2026-07-17T13:26:52","modified_gmt":"2026-07-17T11:26:52","slug":"ai-and-digitalization-in-hazardous-materials-management-opportunities-limitations-and-a-look-ahead","status":"publish","type":"post","link":"https:\/\/www.gesi.de\/en\/ai-and-digitalization-in-hazardous-materials-management-opportunities-limitations-and-a-look-ahead\/","title":{"rendered":"AI and Digitalization in Hazardous Materials Management: Opportunities, Limitations, and a Look Ahead"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Artificial intelligence has also made its way into hazardous materials management: in the processing of safety data sheets (SDS), in classification issues, and in the preparation of risk assessments. The efficiency gains are real. But just as real is the question of where meaningful support ends and where the risk begins of relying on a technology that knows no technical limits.  <\/p>\n\n<h2 class=\"wp-block-heading\">First Things First<\/h2>\n\n<p class=\"wp-block-paragraph\">AI can provide valuable support in hazardous substance management, particularly when large volumes of data need to be processed in a structured manner and recurring tasks need to be automated. It can extract information from safety data sheets, assist with classification issues, and, in the future, link multiple steps together using AI agents. The technical assessment remains the responsibility of the qualified specialist, while legal responsibility lies with the employer.  <\/p>\n\n<h2 class=\"wp-block-heading\">What Can AI Do for Hazardous Materials Management?<\/h2>\n\n<p class=\"wp-block-paragraph\">The most obvious use case is <a href=\"https:\/\/www.gesi.de\/en\/reading-safety-data-sheets\/\">to automatically extract data from SDS PDFs<\/a> instead of entering it manually. Clearly structured information such as classifications, threshold values, <a href=\"https:\/\/www.gesi.de\/en\/determine-storage-classes-with-safety-data-sheets\/\">storage classes<\/a>, and physicochemical properties has long been reliably extracted using rule-based methods. It becomes more challenging with sections containing a lot of continuous text or tables, such as those on ingredients, toxicology, or environmental impacts. This is precisely where AI can usefully complement the rule-based approach.   <\/p>\n\n<p class=\"wp-block-paragraph\">Other areas where AI can already provide support today:<\/p>\n\n<ul class=\"wp-block-list\">\n<li>AI-powered Extraction of Complex Sections from Safety Data Sheets<\/li>\n\n\n\n<li>Assistance with Placement Questions<\/li>\n\n\n\n<li>Additional support in preparing risk <a href=\"https:\/\/www.gesi.de\/en\/efficiency-in-risk-assessments\/\">assessments<\/a><\/li>\n<\/ul>\n\n<p class=\"wp-block-paragraph\">In our risk assessments, we already rely on a structured, catalog-based approach. AI can provide additional support for this process in the future. Of course, the technical evaluation remains the responsibility of the qualified professional in charge.  <\/p>\n\n<h2 class=\"wp-block-heading\">The Next Step: From Individual Task to Agent<\/h2>\n\n<p class=\"wp-block-paragraph\">So far, these applications have mostly focused on individual tasks. The next step involves combining several of them into a workflow that an AI agent controls autonomously. Unlike a chatbot, it doesn\u2019t just respond\u2014it takes action: It accesses stored data, performs multiple steps, and delivers a concrete result.  <\/p>\n\n<p class=\"wp-block-paragraph\">The key factor here is how the agent obtains its data. If it is connected via a controlled interface such as the Model Context Protocol (MCP)\u2014with clearly defined data sources and functions\u2014it can access specific information stored in the system. In this case, the agent does not need to generate values on its own but can, for example, retrieve them directly from the <a href=\"https:\/\/www.gesi.de\/en\/effort-for-the-maintenance-of-a-hazardous-substances-register\/\">hazardous substances inventory<\/a> or a risk assessment. This creates a more reliable data foundation and reduces the risk of statements that sound plausible but are actually incorrect.   <\/p>\n\n<p class=\"wp-block-paragraph\">In the future, more complex, natural-language queries such as the following may also be possible:<\/p>\n\n<p class=\"wp-block-paragraph\"><em>&#8220;Show me all the skin-sensitizing hazardous substances in Warehouse 3.&#8221;<\/em><\/p>\n\n<p class=\"wp-block-paragraph\">or<\/p>\n\n<p class=\"wp-block-paragraph\"><em>&#8220;Create an <\/em><a href=\"https:\/\/www.gesi.de\/erstellung-ueberpruefung-und-freigabe-von-betriebsanweisungen\/\">operating procedure<\/a><em> for hazardous substance XY in the mixing area based on the current GBU.\u201d<\/em><\/p>\n\n<p class=\"wp-block-paragraph\">The second example in particular illustrates that the agent consolidates data from multiple sources, such as risk assessments, the hazardous substances inventory, and the workplace. The agent does not make any independent technical decisions in this process; that remains the responsibility of the qualified specialist.  <\/p>\n\n<h2 class=\"wp-block-heading\">Limits and Interaction: Where People Still Play a Key Role<\/h2>\n\n<p class=\"wp-block-paragraph\">Even though a controlled connection such as MCP ensures that an agent can access specific, defined data, the technical evaluation of that data is a separate task. Whether an activity is safe under the given conditions, which measure is appropriate in a specific case, or how a new regulation affects an existing process\u2014these questions require subject matter expertise, an understanding of the context, and, therefore, continued human judgment. <\/p>\n\n<p class=\"wp-block-paragraph\">Then there is the legal aspect: Under the Hazardous Substances Ordinance (GefStoffV), the employer remains responsible for the risk assessment and the protective measures derived from it, regardless of which tool was used behind the scenes. This responsibility cannot be delegated to either a single AI function or an agent. <\/p>\n\n<p class=\"wp-block-paragraph\">That is why hazardous materials management is not about an \u201ceither\/or\u201d choice between AI and human experts, but rather about collaboration. Reliable, controlled systems handle the structured data processing; the technical assessment and decision-making remain in human hands. It is precisely according to this principle that we at GeSi are continuously expanding our tools: step by step, in areas where AI offers real added value, and always with a reliable foundation in the background.  <\/p>\n\n<p class=\"wp-block-paragraph\">AI is therefore not a replacement, but a support tool. It takes routine tasks off our hands and creates structure. Technical responsibility remains where it belongs.  <\/p>\n\n<h2 class=\"wp-block-heading\">Sources<\/h2>\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.gesetze-im-internet.de\/gefstoffv_2010\/\">[1] Regulation on the Protection against Hazardous Substances (Hazardous Substances Regulation\u2014GefStoffV), current version<\/a><\/p>\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/eur-lex.europa.eu\/legal-content\/DE\/TXT\/?uri=CELEX%3A32006R1907\">[2] Regulation (EC) No. 1907\/2006 (REACH Regulation), EUR-Lex<\/a><\/p>\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/eur-lex.europa.eu\/legal-content\/DE\/TXT\/?uri=CELEX%3A32008R1272\">[3] Regulation (EC) No. 1272\/2008 (CLP Regulation), EUR-Lex<\/a><\/p>\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/www.bsi.bund.de\/SharedDocs\/Downloads\/DE\/BSI\/KI\/Generative_KI-Modelle.pdf?__blob=publicationFile&amp;v=7\">[4] Federal Office for Information Security: Generative AI Models\u2014Opportunities and Risks<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Artificial intelligence has also made its way into hazardous materials management: in the processing of safety data sheets (SDS), in classification issues, and in the preparation of risk assessments. The [&hellip;]<\/p>\n","protected":false},"author":26,"featured_media":52363,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false,"footnotes":""},"categories":[1165],"tags":[1221],"class_list":["post-52412","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-hazardous-substance-administration","tag-gesi4"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AI and Digitalization in Hazardous Materials Management: Opportunities, Limitations, and a Look Ahead - GeSi<\/title>\n<meta name=\"description\" content=\"How can AI support hazardous materials management? 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